{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Transformer MM explainability-ViT.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyP/9xw8HG2FkbQgyW4Dka6b",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/hila-chefer/Transformer-MM-Explainability/blob/main/Transformer_MM_explainability_ViT.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Zj6EnzRyAY5q"
      },
      "source": [
        "# **Transformer MM explainability- ViT (single modality)**"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ej3H_oMmAx3C",
        "outputId": "ec9111e9-886d-415c-f1c5-6a2f51b91a0a"
      },
      "source": [
        "!git clone https://github.com/hila-chefer/Transformer-Explainability.git\n",
        "\n",
        "import os\n",
        "os.chdir(f'./Transformer-Explainability')\n",
        "\n",
        "!pip install -r requirements.txt"
      ],
      "execution_count": 88,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cloning into 'Transformer-Explainability'...\n",
            "remote: Enumerating objects: 338, done.\u001b[K\n",
            "remote: Counting objects: 100% (338/338), done.\u001b[K\n",
            "remote: Compressing objects: 100% (255/255), done.\u001b[K\n",
            "remote: Total 338 (delta 166), reused 180 (delta 69), pack-reused 0\u001b[K\n",
            "Receiving objects: 100% (338/338), 2.87 MiB | 14.69 MiB/s, done.\n",
            "Resolving deltas: 100% (166/166), done.\n",
            "Requirement already satisfied: Pillow>=8.1.1 in /usr/local/lib/python3.7/dist-packages (from -r requirements.txt (line 1)) (8.2.0)\n",
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            "Requirement already satisfied: matplotlib==3.3.2 in /usr/local/lib/python3.7/dist-packages (from -r requirements.txt (line 5)) (3.3.2)\n",
            "Requirement already satisfied: numpy==1.19.2 in /usr/local/lib/python3.7/dist-packages (from -r requirements.txt (line 6)) (1.19.2)\n",
            "Requirement already satisfied: opencv_python==3.4.2.17 in /usr/local/lib/python3.7/dist-packages (from -r requirements.txt (line 7)) (3.4.2.17)\n",
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            "Requirement already satisfied: torch==1.7.0 in /usr/local/lib/python3.7/dist-packages (from -r requirements.txt (line 11)) (1.7.0)\n",
            "Requirement already satisfied: torchvision==0.8.1 in /usr/local/lib/python3.7/dist-packages (from -r requirements.txt (line 12)) (0.8.1)\n",
            "Requirement already satisfied: tqdm==4.51.0 in /usr/local/lib/python3.7/dist-packages (from -r requirements.txt (line 13)) (4.51.0)\n",
            "Requirement already satisfied: transformers==3.5.1 in /usr/local/lib/python3.7/dist-packages (from -r requirements.txt (line 14)) (3.5.1)\n",
            "Requirement already satisfied: utils==1.0.1 in /usr/local/lib/python3.7/dist-packages (from -r requirements.txt (line 15)) (1.0.1)\n",
            "Requirement already satisfied: Pygments>=2.7.4 in /usr/local/lib/python3.7/dist-packages (from -r requirements.txt (line 16)) (2.9.0)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from h5py==2.8.0->-r requirements.txt (line 3)) (1.15.0)\n",
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            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib==3.3.2->-r requirements.txt (line 5)) (1.3.1)\n",
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            "Requirement already satisfied: cycler>=0.10 in /usr/local/lib/python3.7/dist-packages (from matplotlib==3.3.2->-r requirements.txt (line 5)) (0.10.0)\n",
            "Requirement already satisfied: python-dateutil>=2.1 in /usr/local/lib/python3.7/dist-packages (from matplotlib==3.3.2->-r requirements.txt (line 5)) (2.8.1)\n",
            "Requirement already satisfied: tifffile>=2019.7.26 in /usr/local/lib/python3.7/dist-packages (from scikit_image==0.17.2->-r requirements.txt (line 8)) (2021.4.8)\n",
            "Requirement already satisfied: networkx>=2.0 in /usr/local/lib/python3.7/dist-packages (from scikit_image==0.17.2->-r requirements.txt (line 8)) (2.5.1)\n",
            "Requirement already satisfied: PyWavelets>=1.1.1 in /usr/local/lib/python3.7/dist-packages (from scikit_image==0.17.2->-r requirements.txt (line 8)) (1.1.1)\n",
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            "Requirement already satisfied: future in /usr/local/lib/python3.7/dist-packages (from torch==1.7.0->-r requirements.txt (line 11)) (0.16.0)\n",
            "Requirement already satisfied: dataclasses in /usr/local/lib/python3.7/dist-packages (from torch==1.7.0->-r requirements.txt (line 11)) (0.6)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from torch==1.7.0->-r requirements.txt (line 11)) (3.7.4.3)\n",
            "Requirement already satisfied: sacremoses in /usr/local/lib/python3.7/dist-packages (from transformers==3.5.1->-r requirements.txt (line 14)) (0.0.45)\n",
            "Requirement already satisfied: tokenizers==0.9.3 in /usr/local/lib/python3.7/dist-packages (from transformers==3.5.1->-r requirements.txt (line 14)) (0.9.3)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.7/dist-packages (from transformers==3.5.1->-r requirements.txt (line 14)) (3.0.12)\n",
            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.7/dist-packages (from transformers==3.5.1->-r requirements.txt (line 14)) (2019.12.20)\n",
            "Requirement already satisfied: protobuf in /usr/local/lib/python3.7/dist-packages (from transformers==3.5.1->-r requirements.txt (line 14)) (3.12.4)\n",
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            "Requirement already satisfied: decorator<5,>=4.3 in /usr/local/lib/python3.7/dist-packages (from networkx>=2.0->scikit_image==0.17.2->-r requirements.txt (line 8)) (4.4.2)\n",
            "Requirement already satisfied: joblib>=0.11 in /usr/local/lib/python3.7/dist-packages (from scikit-learn->sklearn->-r requirements.txt (line 10)) (1.0.1)\n",
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            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->transformers==3.5.1->-r requirements.txt (line 14)) (3.0.4)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->transformers==3.5.1->-r requirements.txt (line 14)) (2.10)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->transformers==3.5.1->-r requirements.txt (line 14)) (1.24.3)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IdJ4YOiTBtAz"
      },
      "source": [
        "from PIL import Image\n",
        "import torchvision.transforms as transforms\n",
        "import matplotlib.pyplot as plt\n",
        "import torch\n",
        "import numpy as np\n",
        "import cv2"
      ],
      "execution_count": 89,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "cellView": "form",
        "id": "TtqMdXdTEKAP"
      },
      "source": [
        "#@title Imagenet class indices to names\n",
        "%%capture\n",
        "CLS2IDX = {0: 'tench, Tinca tinca',\n",
        " 1: 'goldfish, Carassius auratus',\n",
        " 2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias',\n",
        " 3: 'tiger shark, Galeocerdo cuvieri',\n",
        " 4: 'hammerhead, hammerhead shark',\n",
        " 5: 'electric ray, crampfish, numbfish, torpedo',\n",
        " 6: 'stingray',\n",
        " 7: 'cock',\n",
        " 8: 'hen',\n",
        " 9: 'ostrich, Struthio camelus',\n",
        " 10: 'brambling, Fringilla montifringilla',\n",
        " 11: 'goldfinch, Carduelis carduelis',\n",
        " 12: 'house finch, linnet, Carpodacus mexicanus',\n",
        " 13: 'junco, snowbird',\n",
        " 14: 'indigo bunting, indigo finch, indigo bird, Passerina cyanea',\n",
        " 15: 'robin, American robin, Turdus migratorius',\n",
        " 16: 'bulbul',\n",
        " 17: 'jay',\n",
        " 18: 'magpie',\n",
        " 19: 'chickadee',\n",
        " 20: 'water ouzel, dipper',\n",
        " 21: 'kite',\n",
        " 22: 'bald eagle, American eagle, Haliaeetus leucocephalus',\n",
        " 23: 'vulture',\n",
        " 24: 'great grey owl, great gray owl, Strix nebulosa',\n",
        " 25: 'European fire salamander, Salamandra salamandra',\n",
        " 26: 'common newt, Triturus vulgaris',\n",
        " 27: 'eft',\n",
        " 28: 'spotted salamander, Ambystoma maculatum',\n",
        " 29: 'axolotl, mud puppy, Ambystoma mexicanum',\n",
        " 30: 'bullfrog, Rana catesbeiana',\n",
        " 31: 'tree frog, tree-frog',\n",
        " 32: 'tailed frog, bell toad, ribbed toad, tailed toad, Ascaphus trui',\n",
        " 33: 'loggerhead, loggerhead turtle, Caretta caretta',\n",
        " 34: 'leatherback turtle, leatherback, leathery turtle, Dermochelys coriacea',\n",
        " 35: 'mud turtle',\n",
        " 36: 'terrapin',\n",
        " 37: 'box turtle, box tortoise',\n",
        " 38: 'banded gecko',\n",
        " 39: 'common iguana, iguana, Iguana iguana',\n",
        " 40: 'American chameleon, anole, Anolis carolinensis',\n",
        " 41: 'whiptail, whiptail lizard',\n",
        " 42: 'agama',\n",
        " 43: 'frilled lizard, Chlamydosaurus kingi',\n",
        " 44: 'alligator lizard',\n",
        " 45: 'Gila monster, Heloderma suspectum',\n",
        " 46: 'green lizard, Lacerta viridis',\n",
        " 47: 'African chameleon, Chamaeleo chamaeleon',\n",
        " 48: 'Komodo dragon, Komodo lizard, dragon lizard, giant lizard, Varanus komodoensis',\n",
        " 49: 'African crocodile, Nile crocodile, Crocodylus niloticus',\n",
        " 50: 'American alligator, Alligator mississipiensis',\n",
        " 51: 'triceratops',\n",
        " 52: 'thunder snake, worm snake, Carphophis amoenus',\n",
        " 53: 'ringneck snake, ring-necked snake, ring snake',\n",
        " 54: 'hognose snake, puff adder, sand viper',\n",
        " 55: 'green snake, grass snake',\n",
        " 56: 'king snake, kingsnake',\n",
        " 57: 'garter snake, grass snake',\n",
        " 58: 'water snake',\n",
        " 59: 'vine snake',\n",
        " 60: 'night snake, Hypsiglena torquata',\n",
        " 61: 'boa constrictor, Constrictor constrictor',\n",
        " 62: 'rock python, rock snake, Python sebae',\n",
        " 63: 'Indian cobra, Naja naja',\n",
        " 64: 'green mamba',\n",
        " 65: 'sea snake',\n",
        " 66: 'horned viper, cerastes, sand viper, horned asp, Cerastes cornutus',\n",
        " 67: 'diamondback, diamondback rattlesnake, Crotalus adamanteus',\n",
        " 68: 'sidewinder, horned rattlesnake, Crotalus cerastes',\n",
        " 69: 'trilobite',\n",
        " 70: 'harvestman, daddy longlegs, Phalangium opilio',\n",
        " 71: 'scorpion',\n",
        " 72: 'black and gold garden spider, Argiope aurantia',\n",
        " 73: 'barn spider, Araneus cavaticus',\n",
        " 74: 'garden spider, Aranea diademata',\n",
        " 75: 'black widow, Latrodectus mactans',\n",
        " 76: 'tarantula',\n",
        " 77: 'wolf spider, hunting spider',\n",
        " 78: 'tick',\n",
        " 79: 'centipede',\n",
        " 80: 'black grouse',\n",
        " 81: 'ptarmigan',\n",
        " 82: 'ruffed grouse, partridge, Bonasa umbellus',\n",
        " 83: 'prairie chicken, prairie grouse, prairie fowl',\n",
        " 84: 'peacock',\n",
        " 85: 'quail',\n",
        " 86: 'partridge',\n",
        " 87: 'African grey, African gray, Psittacus erithacus',\n",
        " 88: 'macaw',\n",
        " 89: 'sulphur-crested cockatoo, Kakatoe galerita, Cacatua galerita',\n",
        " 90: 'lorikeet',\n",
        " 91: 'coucal',\n",
        " 92: 'bee eater',\n",
        " 93: 'hornbill',\n",
        " 94: 'hummingbird',\n",
        " 95: 'jacamar',\n",
        " 96: 'toucan',\n",
        " 97: 'drake',\n",
        " 98: 'red-breasted merganser, Mergus serrator',\n",
        " 99: 'goose',\n",
        " 100: 'black swan, Cygnus atratus',\n",
        " 101: 'tusker',\n",
        " 102: 'echidna, spiny anteater, anteater',\n",
        " 103: 'platypus, duckbill, duckbilled platypus, duck-billed platypus, Ornithorhynchus anatinus',\n",
        " 104: 'wallaby, brush kangaroo',\n",
        " 105: 'koala, koala bear, kangaroo bear, native bear, Phascolarctos cinereus',\n",
        " 106: 'wombat',\n",
        " 107: 'jellyfish',\n",
        " 108: 'sea anemone, anemone',\n",
        " 109: 'brain coral',\n",
        " 110: 'flatworm, platyhelminth',\n",
        " 111: 'nematode, nematode worm, roundworm',\n",
        " 112: 'conch',\n",
        " 113: 'snail',\n",
        " 114: 'slug',\n",
        " 115: 'sea slug, nudibranch',\n",
        " 116: 'chiton, coat-of-mail shell, sea cradle, polyplacophore',\n",
        " 117: 'chambered nautilus, pearly nautilus, nautilus',\n",
        " 118: 'Dungeness crab, Cancer magister',\n",
        " 119: 'rock crab, Cancer irroratus',\n",
        " 120: 'fiddler crab',\n",
        " 121: 'king crab, Alaska crab, Alaskan king crab, Alaska king crab, Paralithodes camtschatica',\n",
        " 122: 'American lobster, Northern lobster, Maine lobster, Homarus americanus',\n",
        " 123: 'spiny lobster, langouste, rock lobster, crawfish, crayfish, sea crawfish',\n",
        " 124: 'crayfish, crawfish, crawdad, crawdaddy',\n",
        " 125: 'hermit crab',\n",
        " 126: 'isopod',\n",
        " 127: 'white stork, Ciconia ciconia',\n",
        " 128: 'black stork, Ciconia nigra',\n",
        " 129: 'spoonbill',\n",
        " 130: 'flamingo',\n",
        " 131: 'little blue heron, Egretta caerulea',\n",
        " 132: 'American egret, great white heron, Egretta albus',\n",
        " 133: 'bittern',\n",
        " 134: 'crane',\n",
        " 135: 'limpkin, Aramus pictus',\n",
        " 136: 'European gallinule, Porphyrio porphyrio',\n",
        " 137: 'American coot, marsh hen, mud hen, water hen, Fulica americana',\n",
        " 138: 'bustard',\n",
        " 139: 'ruddy turnstone, Arenaria interpres',\n",
        " 140: 'red-backed sandpiper, dunlin, Erolia alpina',\n",
        " 141: 'redshank, Tringa totanus',\n",
        " 142: 'dowitcher',\n",
        " 143: 'oystercatcher, oyster catcher',\n",
        " 144: 'pelican',\n",
        " 145: 'king penguin, Aptenodytes patagonica',\n",
        " 146: 'albatross, mollymawk',\n",
        " 147: 'grey whale, gray whale, devilfish, Eschrichtius gibbosus, Eschrichtius robustus',\n",
        " 148: 'killer whale, killer, orca, grampus, sea wolf, Orcinus orca',\n",
        " 149: 'dugong, Dugong dugon',\n",
        " 150: 'sea lion',\n",
        " 151: 'Chihuahua',\n",
        " 152: 'Japanese spaniel',\n",
        " 153: 'Maltese dog, Maltese terrier, Maltese',\n",
        " 154: 'Pekinese, Pekingese, Peke',\n",
        " 155: 'Shih-Tzu',\n",
        " 156: 'Blenheim spaniel',\n",
        " 157: 'papillon',\n",
        " 158: 'toy terrier',\n",
        " 159: 'Rhodesian ridgeback',\n",
        " 160: 'Afghan hound, Afghan',\n",
        " 161: 'basset, basset hound',\n",
        " 162: 'beagle',\n",
        " 163: 'bloodhound, sleuthhound',\n",
        " 164: 'bluetick',\n",
        " 165: 'black-and-tan coonhound',\n",
        " 166: 'Walker hound, Walker foxhound',\n",
        " 167: 'English foxhound',\n",
        " 168: 'redbone',\n",
        " 169: 'borzoi, Russian wolfhound',\n",
        " 170: 'Irish wolfhound',\n",
        " 171: 'Italian greyhound',\n",
        " 172: 'whippet',\n",
        " 173: 'Ibizan hound, Ibizan Podenco',\n",
        " 174: 'Norwegian elkhound, elkhound',\n",
        " 175: 'otterhound, otter hound',\n",
        " 176: 'Saluki, gazelle hound',\n",
        " 177: 'Scottish deerhound, deerhound',\n",
        " 178: 'Weimaraner',\n",
        " 179: 'Staffordshire bullterrier, Staffordshire bull terrier',\n",
        " 180: 'American Staffordshire terrier, Staffordshire terrier, American pit bull terrier, pit bull terrier',\n",
        " 181: 'Bedlington terrier',\n",
        " 182: 'Border terrier',\n",
        " 183: 'Kerry blue terrier',\n",
        " 184: 'Irish terrier',\n",
        " 185: 'Norfolk terrier',\n",
        " 186: 'Norwich terrier',\n",
        " 187: 'Yorkshire terrier',\n",
        " 188: 'wire-haired fox terrier',\n",
        " 189: 'Lakeland terrier',\n",
        " 190: 'Sealyham terrier, Sealyham',\n",
        " 191: 'Airedale, Airedale terrier',\n",
        " 192: 'cairn, cairn terrier',\n",
        " 193: 'Australian terrier',\n",
        " 194: 'Dandie Dinmont, Dandie Dinmont terrier',\n",
        " 195: 'Boston bull, Boston terrier',\n",
        " 196: 'miniature schnauzer',\n",
        " 197: 'giant schnauzer',\n",
        " 198: 'standard schnauzer',\n",
        " 199: 'Scotch terrier, Scottish terrier, Scottie',\n",
        " 200: 'Tibetan terrier, chrysanthemum dog',\n",
        " 201: 'silky terrier, Sydney silky',\n",
        " 202: 'soft-coated wheaten terrier',\n",
        " 203: 'West Highland white terrier',\n",
        " 204: 'Lhasa, Lhasa apso',\n",
        " 205: 'flat-coated retriever',\n",
        " 206: 'curly-coated retriever',\n",
        " 207: 'golden retriever',\n",
        " 208: 'Labrador retriever',\n",
        " 209: 'Chesapeake Bay retriever',\n",
        " 210: 'German short-haired pointer',\n",
        " 211: 'vizsla, Hungarian pointer',\n",
        " 212: 'English setter',\n",
        " 213: 'Irish setter, red setter',\n",
        " 214: 'Gordon setter',\n",
        " 215: 'Brittany spaniel',\n",
        " 216: 'clumber, clumber spaniel',\n",
        " 217: 'English springer, English springer spaniel',\n",
        " 218: 'Welsh springer spaniel',\n",
        " 219: 'cocker spaniel, English cocker spaniel, cocker',\n",
        " 220: 'Sussex spaniel',\n",
        " 221: 'Irish water spaniel',\n",
        " 222: 'kuvasz',\n",
        " 223: 'schipperke',\n",
        " 224: 'groenendael',\n",
        " 225: 'malinois',\n",
        " 226: 'briard',\n",
        " 227: 'kelpie',\n",
        " 228: 'komondor',\n",
        " 229: 'Old English sheepdog, bobtail',\n",
        " 230: 'Shetland sheepdog, Shetland sheep dog, Shetland',\n",
        " 231: 'collie',\n",
        " 232: 'Border collie',\n",
        " 233: 'Bouvier des Flandres, Bouviers des Flandres',\n",
        " 234: 'Rottweiler',\n",
        " 235: 'German shepherd, German shepherd dog, German police dog, alsatian',\n",
        " 236: 'Doberman, Doberman pinscher',\n",
        " 237: 'miniature pinscher',\n",
        " 238: 'Greater Swiss Mountain dog',\n",
        " 239: 'Bernese mountain dog',\n",
        " 240: 'Appenzeller',\n",
        " 241: 'EntleBucher',\n",
        " 242: 'boxer',\n",
        " 243: 'bull mastiff',\n",
        " 244: 'Tibetan mastiff',\n",
        " 245: 'French bulldog',\n",
        " 246: 'Great Dane',\n",
        " 247: 'Saint Bernard, St Bernard',\n",
        " 248: 'Eskimo dog, husky',\n",
        " 249: 'malamute, malemute, Alaskan malamute',\n",
        " 250: 'Siberian husky',\n",
        " 251: 'dalmatian, coach dog, carriage dog',\n",
        " 252: 'affenpinscher, monkey pinscher, monkey dog',\n",
        " 253: 'basenji',\n",
        " 254: 'pug, pug-dog',\n",
        " 255: 'Leonberg',\n",
        " 256: 'Newfoundland, Newfoundland dog',\n",
        " 257: 'Great Pyrenees',\n",
        " 258: 'Samoyed, Samoyede',\n",
        " 259: 'Pomeranian',\n",
        " 260: 'chow, chow chow',\n",
        " 261: 'keeshond',\n",
        " 262: 'Brabancon griffon',\n",
        " 263: 'Pembroke, Pembroke Welsh corgi',\n",
        " 264: 'Cardigan, Cardigan Welsh corgi',\n",
        " 265: 'toy poodle',\n",
        " 266: 'miniature poodle',\n",
        " 267: 'standard poodle',\n",
        " 268: 'Mexican hairless',\n",
        " 269: 'timber wolf, grey wolf, gray wolf, Canis lupus',\n",
        " 270: 'white wolf, Arctic wolf, Canis lupus tundrarum',\n",
        " 271: 'red wolf, maned wolf, Canis rufus, Canis niger',\n",
        " 272: 'coyote, prairie wolf, brush wolf, Canis latrans',\n",
        " 273: 'dingo, warrigal, warragal, Canis dingo',\n",
        " 274: 'dhole, Cuon alpinus',\n",
        " 275: 'African hunting dog, hyena dog, Cape hunting dog, Lycaon pictus',\n",
        " 276: 'hyena, hyaena',\n",
        " 277: 'red fox, Vulpes vulpes',\n",
        " 278: 'kit fox, Vulpes macrotis',\n",
        " 279: 'Arctic fox, white fox, Alopex lagopus',\n",
        " 280: 'grey fox, gray fox, Urocyon cinereoargenteus',\n",
        " 281: 'tabby, tabby cat',\n",
        " 282: 'tiger cat',\n",
        " 283: 'Persian cat',\n",
        " 284: 'Siamese cat, Siamese',\n",
        " 285: 'Egyptian cat',\n",
        " 286: 'cougar, puma, catamount, mountain lion, painter, panther, Felis concolor',\n",
        " 287: 'lynx, catamount',\n",
        " 288: 'leopard, Panthera pardus',\n",
        " 289: 'snow leopard, ounce, Panthera uncia',\n",
        " 290: 'jaguar, panther, Panthera onca, Felis onca',\n",
        " 291: 'lion, king of beasts, Panthera leo',\n",
        " 292: 'tiger, Panthera tigris',\n",
        " 293: 'cheetah, chetah, Acinonyx jubatus',\n",
        " 294: 'brown bear, bruin, Ursus arctos',\n",
        " 295: 'American black bear, black bear, Ursus americanus, Euarctos americanus',\n",
        " 296: 'ice bear, polar bear, Ursus Maritimus, Thalarctos maritimus',\n",
        " 297: 'sloth bear, Melursus ursinus, Ursus ursinus',\n",
        " 298: 'mongoose',\n",
        " 299: 'meerkat, mierkat',\n",
        " 300: 'tiger beetle',\n",
        " 301: 'ladybug, ladybeetle, lady beetle, ladybird, ladybird beetle',\n",
        " 302: 'ground beetle, carabid beetle',\n",
        " 303: 'long-horned beetle, longicorn, longicorn beetle',\n",
        " 304: 'leaf beetle, chrysomelid',\n",
        " 305: 'dung beetle',\n",
        " 306: 'rhinoceros beetle',\n",
        " 307: 'weevil',\n",
        " 308: 'fly',\n",
        " 309: 'bee',\n",
        " 310: 'ant, emmet, pismire',\n",
        " 311: 'grasshopper, hopper',\n",
        " 312: 'cricket',\n",
        " 313: 'walking stick, walkingstick, stick insect',\n",
        " 314: 'cockroach, roach',\n",
        " 315: 'mantis, mantid',\n",
        " 316: 'cicada, cicala',\n",
        " 317: 'leafhopper',\n",
        " 318: 'lacewing, lacewing fly',\n",
        " 319: \"dragonfly, darning needle, devil's darning needle, sewing needle, snake feeder, snake doctor, mosquito hawk, skeeter hawk\",\n",
        " 320: 'damselfly',\n",
        " 321: 'admiral',\n",
        " 322: 'ringlet, ringlet butterfly',\n",
        " 323: 'monarch, monarch butterfly, milkweed butterfly, Danaus plexippus',\n",
        " 324: 'cabbage butterfly',\n",
        " 325: 'sulphur butterfly, sulfur butterfly',\n",
        " 326: 'lycaenid, lycaenid butterfly',\n",
        " 327: 'starfish, sea star',\n",
        " 328: 'sea urchin',\n",
        " 329: 'sea cucumber, holothurian',\n",
        " 330: 'wood rabbit, cottontail, cottontail rabbit',\n",
        " 331: 'hare',\n",
        " 332: 'Angora, Angora rabbit',\n",
        " 333: 'hamster',\n",
        " 334: 'porcupine, hedgehog',\n",
        " 335: 'fox squirrel, eastern fox squirrel, Sciurus niger',\n",
        " 336: 'marmot',\n",
        " 337: 'beaver',\n",
        " 338: 'guinea pig, Cavia cobaya',\n",
        " 339: 'sorrel',\n",
        " 340: 'zebra',\n",
        " 341: 'hog, pig, grunter, squealer, Sus scrofa',\n",
        " 342: 'wild boar, boar, Sus scrofa',\n",
        " 343: 'warthog',\n",
        " 344: 'hippopotamus, hippo, river horse, Hippopotamus amphibius',\n",
        " 345: 'ox',\n",
        " 346: 'water buffalo, water ox, Asiatic buffalo, Bubalus bubalis',\n",
        " 347: 'bison',\n",
        " 348: 'ram, tup',\n",
        " 349: 'bighorn, bighorn sheep, cimarron, Rocky Mountain bighorn, Rocky Mountain sheep, Ovis canadensis',\n",
        " 350: 'ibex, Capra ibex',\n",
        " 351: 'hartebeest',\n",
        " 352: 'impala, Aepyceros melampus',\n",
        " 353: 'gazelle',\n",
        " 354: 'Arabian camel, dromedary, Camelus dromedarius',\n",
        " 355: 'llama',\n",
        " 356: 'weasel',\n",
        " 357: 'mink',\n",
        " 358: 'polecat, fitch, foulmart, foumart, Mustela putorius',\n",
        " 359: 'black-footed ferret, ferret, Mustela nigripes',\n",
        " 360: 'otter',\n",
        " 361: 'skunk, polecat, wood pussy',\n",
        " 362: 'badger',\n",
        " 363: 'armadillo',\n",
        " 364: 'three-toed sloth, ai, Bradypus tridactylus',\n",
        " 365: 'orangutan, orang, orangutang, Pongo pygmaeus',\n",
        " 366: 'gorilla, Gorilla gorilla',\n",
        " 367: 'chimpanzee, chimp, Pan troglodytes',\n",
        " 368: 'gibbon, Hylobates lar',\n",
        " 369: 'siamang, Hylobates syndactylus, Symphalangus syndactylus',\n",
        " 370: 'guenon, guenon monkey',\n",
        " 371: 'patas, hussar monkey, Erythrocebus patas',\n",
        " 372: 'baboon',\n",
        " 373: 'macaque',\n",
        " 374: 'langur',\n",
        " 375: 'colobus, colobus monkey',\n",
        " 376: 'proboscis monkey, Nasalis larvatus',\n",
        " 377: 'marmoset',\n",
        " 378: 'capuchin, ringtail, Cebus capucinus',\n",
        " 379: 'howler monkey, howler',\n",
        " 380: 'titi, titi monkey',\n",
        " 381: 'spider monkey, Ateles geoffroyi',\n",
        " 382: 'squirrel monkey, Saimiri sciureus',\n",
        " 383: 'Madagascar cat, ring-tailed lemur, Lemur catta',\n",
        " 384: 'indri, indris, Indri indri, Indri brevicaudatus',\n",
        " 385: 'Indian elephant, Elephas maximus',\n",
        " 386: 'African elephant, Loxodonta africana',\n",
        " 387: 'lesser panda, red panda, panda, bear cat, cat bear, Ailurus fulgens',\n",
        " 388: 'giant panda, panda, panda bear, coon bear, Ailuropoda melanoleuca',\n",
        " 389: 'barracouta, snoek',\n",
        " 390: 'eel',\n",
        " 391: 'coho, cohoe, coho salmon, blue jack, silver salmon, Oncorhynchus kisutch',\n",
        " 392: 'rock beauty, Holocanthus tricolor',\n",
        " 393: 'anemone fish',\n",
        " 394: 'sturgeon',\n",
        " 395: 'gar, garfish, garpike, billfish, Lepisosteus osseus',\n",
        " 396: 'lionfish',\n",
        " 397: 'puffer, pufferfish, blowfish, globefish',\n",
        " 398: 'abacus',\n",
        " 399: 'abaya',\n",
        " 400: \"academic gown, academic robe, judge's robe\",\n",
        " 401: 'accordion, piano accordion, squeeze box',\n",
        " 402: 'acoustic guitar',\n",
        " 403: 'aircraft carrier, carrier, flattop, attack aircraft carrier',\n",
        " 404: 'airliner',\n",
        " 405: 'airship, dirigible',\n",
        " 406: 'altar',\n",
        " 407: 'ambulance',\n",
        " 408: 'amphibian, amphibious vehicle',\n",
        " 409: 'analog clock',\n",
        " 410: 'apiary, bee house',\n",
        " 411: 'apron',\n",
        " 412: 'ashcan, trash can, garbage can, wastebin, ash bin, ash-bin, ashbin, dustbin, trash barrel, trash bin',\n",
        " 413: 'assault rifle, assault gun',\n",
        " 414: 'backpack, back pack, knapsack, packsack, rucksack, haversack',\n",
        " 415: 'bakery, bakeshop, bakehouse',\n",
        " 416: 'balance beam, beam',\n",
        " 417: 'balloon',\n",
        " 418: 'ballpoint, ballpoint pen, ballpen, Biro',\n",
        " 419: 'Band Aid',\n",
        " 420: 'banjo',\n",
        " 421: 'bannister, banister, balustrade, balusters, handrail',\n",
        " 422: 'barbell',\n",
        " 423: 'barber chair',\n",
        " 424: 'barbershop',\n",
        " 425: 'barn',\n",
        " 426: 'barometer',\n",
        " 427: 'barrel, cask',\n",
        " 428: 'barrow, garden cart, lawn cart, wheelbarrow',\n",
        " 429: 'baseball',\n",
        " 430: 'basketball',\n",
        " 431: 'bassinet',\n",
        " 432: 'bassoon',\n",
        " 433: 'bathing cap, swimming cap',\n",
        " 434: 'bath towel',\n",
        " 435: 'bathtub, bathing tub, bath, tub',\n",
        " 436: 'beach wagon, station wagon, wagon, estate car, beach waggon, station waggon, waggon',\n",
        " 437: 'beacon, lighthouse, beacon light, pharos',\n",
        " 438: 'beaker',\n",
        " 439: 'bearskin, busby, shako',\n",
        " 440: 'beer bottle',\n",
        " 441: 'beer glass',\n",
        " 442: 'bell cote, bell cot',\n",
        " 443: 'bib',\n",
        " 444: 'bicycle-built-for-two, tandem bicycle, tandem',\n",
        " 445: 'bikini, two-piece',\n",
        " 446: 'binder, ring-binder',\n",
        " 447: 'binoculars, field glasses, opera glasses',\n",
        " 448: 'birdhouse',\n",
        " 449: 'boathouse',\n",
        " 450: 'bobsled, bobsleigh, bob',\n",
        " 451: 'bolo tie, bolo, bola tie, bola',\n",
        " 452: 'bonnet, poke bonnet',\n",
        " 453: 'bookcase',\n",
        " 454: 'bookshop, bookstore, bookstall',\n",
        " 455: 'bottlecap',\n",
        " 456: 'bow',\n",
        " 457: 'bow tie, bow-tie, bowtie',\n",
        " 458: 'brass, memorial tablet, plaque',\n",
        " 459: 'brassiere, bra, bandeau',\n",
        " 460: 'breakwater, groin, groyne, mole, bulwark, seawall, jetty',\n",
        " 461: 'breastplate, aegis, egis',\n",
        " 462: 'broom',\n",
        " 463: 'bucket, pail',\n",
        " 464: 'buckle',\n",
        " 465: 'bulletproof vest',\n",
        " 466: 'bullet train, bullet',\n",
        " 467: 'butcher shop, meat market',\n",
        " 468: 'cab, hack, taxi, taxicab',\n",
        " 469: 'caldron, cauldron',\n",
        " 470: 'candle, taper, wax light',\n",
        " 471: 'cannon',\n",
        " 472: 'canoe',\n",
        " 473: 'can opener, tin opener',\n",
        " 474: 'cardigan',\n",
        " 475: 'car mirror',\n",
        " 476: 'carousel, carrousel, merry-go-round, roundabout, whirligig',\n",
        " 477: \"carpenter's kit, tool kit\",\n",
        " 478: 'carton',\n",
        " 479: 'car wheel',\n",
        " 480: 'cash machine, cash dispenser, automated teller machine, automatic teller machine, automated teller, automatic teller, ATM',\n",
        " 481: 'cassette',\n",
        " 482: 'cassette player',\n",
        " 483: 'castle',\n",
        " 484: 'catamaran',\n",
        " 485: 'CD player',\n",
        " 486: 'cello, violoncello',\n",
        " 487: 'cellular telephone, cellular phone, cellphone, cell, mobile phone',\n",
        " 488: 'chain',\n",
        " 489: 'chainlink fence',\n",
        " 490: 'chain mail, ring mail, mail, chain armor, chain armour, ring armor, ring armour',\n",
        " 491: 'chain saw, chainsaw',\n",
        " 492: 'chest',\n",
        " 493: 'chiffonier, commode',\n",
        " 494: 'chime, bell, gong',\n",
        " 495: 'china cabinet, china closet',\n",
        " 496: 'Christmas stocking',\n",
        " 497: 'church, church building',\n",
        " 498: 'cinema, movie theater, movie theatre, movie house, picture palace',\n",
        " 499: 'cleaver, meat cleaver, chopper',\n",
        " 500: 'cliff dwelling',\n",
        " 501: 'cloak',\n",
        " 502: 'clog, geta, patten, sabot',\n",
        " 503: 'cocktail shaker',\n",
        " 504: 'coffee mug',\n",
        " 505: 'coffeepot',\n",
        " 506: 'coil, spiral, volute, whorl, helix',\n",
        " 507: 'combination lock',\n",
        " 508: 'computer keyboard, keypad',\n",
        " 509: 'confectionery, confectionary, candy store',\n",
        " 510: 'container ship, containership, container vessel',\n",
        " 511: 'convertible',\n",
        " 512: 'corkscrew, bottle screw',\n",
        " 513: 'cornet, horn, trumpet, trump',\n",
        " 514: 'cowboy boot',\n",
        " 515: 'cowboy hat, ten-gallon hat',\n",
        " 516: 'cradle',\n",
        " 517: 'crane',\n",
        " 518: 'crash helmet',\n",
        " 519: 'crate',\n",
        " 520: 'crib, cot',\n",
        " 521: 'Crock Pot',\n",
        " 522: 'croquet ball',\n",
        " 523: 'crutch',\n",
        " 524: 'cuirass',\n",
        " 525: 'dam, dike, dyke',\n",
        " 526: 'desk',\n",
        " 527: 'desktop computer',\n",
        " 528: 'dial telephone, dial phone',\n",
        " 529: 'diaper, nappy, napkin',\n",
        " 530: 'digital clock',\n",
        " 531: 'digital watch',\n",
        " 532: 'dining table, board',\n",
        " 533: 'dishrag, dishcloth',\n",
        " 534: 'dishwasher, dish washer, dishwashing machine',\n",
        " 535: 'disk brake, disc brake',\n",
        " 536: 'dock, dockage, docking facility',\n",
        " 537: 'dogsled, dog sled, dog sleigh',\n",
        " 538: 'dome',\n",
        " 539: 'doormat, welcome mat',\n",
        " 540: 'drilling platform, offshore rig',\n",
        " 541: 'drum, membranophone, tympan',\n",
        " 542: 'drumstick',\n",
        " 543: 'dumbbell',\n",
        " 544: 'Dutch oven',\n",
        " 545: 'electric fan, blower',\n",
        " 546: 'electric guitar',\n",
        " 547: 'electric locomotive',\n",
        " 548: 'entertainment center',\n",
        " 549: 'envelope',\n",
        " 550: 'espresso maker',\n",
        " 551: 'face powder',\n",
        " 552: 'feather boa, boa',\n",
        " 553: 'file, file cabinet, filing cabinet',\n",
        " 554: 'fireboat',\n",
        " 555: 'fire engine, fire truck',\n",
        " 556: 'fire screen, fireguard',\n",
        " 557: 'flagpole, flagstaff',\n",
        " 558: 'flute, transverse flute',\n",
        " 559: 'folding chair',\n",
        " 560: 'football helmet',\n",
        " 561: 'forklift',\n",
        " 562: 'fountain',\n",
        " 563: 'fountain pen',\n",
        " 564: 'four-poster',\n",
        " 565: 'freight car',\n",
        " 566: 'French horn, horn',\n",
        " 567: 'frying pan, frypan, skillet',\n",
        " 568: 'fur coat',\n",
        " 569: 'garbage truck, dustcart',\n",
        " 570: 'gasmask, respirator, gas helmet',\n",
        " 571: 'gas pump, gasoline pump, petrol pump, island dispenser',\n",
        " 572: 'goblet',\n",
        " 573: 'go-kart',\n",
        " 574: 'golf ball',\n",
        " 575: 'golfcart, golf cart',\n",
        " 576: 'gondola',\n",
        " 577: 'gong, tam-tam',\n",
        " 578: 'gown',\n",
        " 579: 'grand piano, grand',\n",
        " 580: 'greenhouse, nursery, glasshouse',\n",
        " 581: 'grille, radiator grille',\n",
        " 582: 'grocery store, grocery, food market, market',\n",
        " 583: 'guillotine',\n",
        " 584: 'hair slide',\n",
        " 585: 'hair spray',\n",
        " 586: 'half track',\n",
        " 587: 'hammer',\n",
        " 588: 'hamper',\n",
        " 589: 'hand blower, blow dryer, blow drier, hair dryer, hair drier',\n",
        " 590: 'hand-held computer, hand-held microcomputer',\n",
        " 591: 'handkerchief, hankie, hanky, hankey',\n",
        " 592: 'hard disc, hard disk, fixed disk',\n",
        " 593: 'harmonica, mouth organ, harp, mouth harp',\n",
        " 594: 'harp',\n",
        " 595: 'harvester, reaper',\n",
        " 596: 'hatchet',\n",
        " 597: 'holster',\n",
        " 598: 'home theater, home theatre',\n",
        " 599: 'honeycomb',\n",
        " 600: 'hook, claw',\n",
        " 601: 'hoopskirt, crinoline',\n",
        " 602: 'horizontal bar, high bar',\n",
        " 603: 'horse cart, horse-cart',\n",
        " 604: 'hourglass',\n",
        " 605: 'iPod',\n",
        " 606: 'iron, smoothing iron',\n",
        " 607: \"jack-o'-lantern\",\n",
        " 608: 'jean, blue jean, denim',\n",
        " 609: 'jeep, landrover',\n",
        " 610: 'jersey, T-shirt, tee shirt',\n",
        " 611: 'jigsaw puzzle',\n",
        " 612: 'jinrikisha, ricksha, rickshaw',\n",
        " 613: 'joystick',\n",
        " 614: 'kimono',\n",
        " 615: 'knee pad',\n",
        " 616: 'knot',\n",
        " 617: 'lab coat, laboratory coat',\n",
        " 618: 'ladle',\n",
        " 619: 'lampshade, lamp shade',\n",
        " 620: 'laptop, laptop computer',\n",
        " 621: 'lawn mower, mower',\n",
        " 622: 'lens cap, lens cover',\n",
        " 623: 'letter opener, paper knife, paperknife',\n",
        " 624: 'library',\n",
        " 625: 'lifeboat',\n",
        " 626: 'lighter, light, igniter, ignitor',\n",
        " 627: 'limousine, limo',\n",
        " 628: 'liner, ocean liner',\n",
        " 629: 'lipstick, lip rouge',\n",
        " 630: 'Loafer',\n",
        " 631: 'lotion',\n",
        " 632: 'loudspeaker, speaker, speaker unit, loudspeaker system, speaker system',\n",
        " 633: \"loupe, jeweler's loupe\",\n",
        " 634: 'lumbermill, sawmill',\n",
        " 635: 'magnetic compass',\n",
        " 636: 'mailbag, postbag',\n",
        " 637: 'mailbox, letter box',\n",
        " 638: 'maillot',\n",
        " 639: 'maillot, tank suit',\n",
        " 640: 'manhole cover',\n",
        " 641: 'maraca',\n",
        " 642: 'marimba, xylophone',\n",
        " 643: 'mask',\n",
        " 644: 'matchstick',\n",
        " 645: 'maypole',\n",
        " 646: 'maze, labyrinth',\n",
        " 647: 'measuring cup',\n",
        " 648: 'medicine chest, medicine cabinet',\n",
        " 649: 'megalith, megalithic structure',\n",
        " 650: 'microphone, mike',\n",
        " 651: 'microwave, microwave oven',\n",
        " 652: 'military uniform',\n",
        " 653: 'milk can',\n",
        " 654: 'minibus',\n",
        " 655: 'miniskirt, mini',\n",
        " 656: 'minivan',\n",
        " 657: 'missile',\n",
        " 658: 'mitten',\n",
        " 659: 'mixing bowl',\n",
        " 660: 'mobile home, manufactured home',\n",
        " 661: 'Model T',\n",
        " 662: 'modem',\n",
        " 663: 'monastery',\n",
        " 664: 'monitor',\n",
        " 665: 'moped',\n",
        " 666: 'mortar',\n",
        " 667: 'mortarboard',\n",
        " 668: 'mosque',\n",
        " 669: 'mosquito net',\n",
        " 670: 'motor scooter, scooter',\n",
        " 671: 'mountain bike, all-terrain bike, off-roader',\n",
        " 672: 'mountain tent',\n",
        " 673: 'mouse, computer mouse',\n",
        " 674: 'mousetrap',\n",
        " 675: 'moving van',\n",
        " 676: 'muzzle',\n",
        " 677: 'nail',\n",
        " 678: 'neck brace',\n",
        " 679: 'necklace',\n",
        " 680: 'nipple',\n",
        " 681: 'notebook, notebook computer',\n",
        " 682: 'obelisk',\n",
        " 683: 'oboe, hautboy, hautbois',\n",
        " 684: 'ocarina, sweet potato',\n",
        " 685: 'odometer, hodometer, mileometer, milometer',\n",
        " 686: 'oil filter',\n",
        " 687: 'organ, pipe organ',\n",
        " 688: 'oscilloscope, scope, cathode-ray oscilloscope, CRO',\n",
        " 689: 'overskirt',\n",
        " 690: 'oxcart',\n",
        " 691: 'oxygen mask',\n",
        " 692: 'packet',\n",
        " 693: 'paddle, boat paddle',\n",
        " 694: 'paddlewheel, paddle wheel',\n",
        " 695: 'padlock',\n",
        " 696: 'paintbrush',\n",
        " 697: \"pajama, pyjama, pj's, jammies\",\n",
        " 698: 'palace',\n",
        " 699: 'panpipe, pandean pipe, syrinx',\n",
        " 700: 'paper towel',\n",
        " 701: 'parachute, chute',\n",
        " 702: 'parallel bars, bars',\n",
        " 703: 'park bench',\n",
        " 704: 'parking meter',\n",
        " 705: 'passenger car, coach, carriage',\n",
        " 706: 'patio, terrace',\n",
        " 707: 'pay-phone, pay-station',\n",
        " 708: 'pedestal, plinth, footstall',\n",
        " 709: 'pencil box, pencil case',\n",
        " 710: 'pencil sharpener',\n",
        " 711: 'perfume, essence',\n",
        " 712: 'Petri dish',\n",
        " 713: 'photocopier',\n",
        " 714: 'pick, plectrum, plectron',\n",
        " 715: 'pickelhaube',\n",
        " 716: 'picket fence, paling',\n",
        " 717: 'pickup, pickup truck',\n",
        " 718: 'pier',\n",
        " 719: 'piggy bank, penny bank',\n",
        " 720: 'pill bottle',\n",
        " 721: 'pillow',\n",
        " 722: 'ping-pong ball',\n",
        " 723: 'pinwheel',\n",
        " 724: 'pirate, pirate ship',\n",
        " 725: 'pitcher, ewer',\n",
        " 726: \"plane, carpenter's plane, woodworking plane\",\n",
        " 727: 'planetarium',\n",
        " 728: 'plastic bag',\n",
        " 729: 'plate rack',\n",
        " 730: 'plow, plough',\n",
        " 731: \"plunger, plumber's helper\",\n",
        " 732: 'Polaroid camera, Polaroid Land camera',\n",
        " 733: 'pole',\n",
        " 734: 'police van, police wagon, paddy wagon, patrol wagon, wagon, black Maria',\n",
        " 735: 'poncho',\n",
        " 736: 'pool table, billiard table, snooker table',\n",
        " 737: 'pop bottle, soda bottle',\n",
        " 738: 'pot, flowerpot',\n",
        " 739: \"potter's wheel\",\n",
        " 740: 'power drill',\n",
        " 741: 'prayer rug, prayer mat',\n",
        " 742: 'printer',\n",
        " 743: 'prison, prison house',\n",
        " 744: 'projectile, missile',\n",
        " 745: 'projector',\n",
        " 746: 'puck, hockey puck',\n",
        " 747: 'punching bag, punch bag, punching ball, punchball',\n",
        " 748: 'purse',\n",
        " 749: 'quill, quill pen',\n",
        " 750: 'quilt, comforter, comfort, puff',\n",
        " 751: 'racer, race car, racing car',\n",
        " 752: 'racket, racquet',\n",
        " 753: 'radiator',\n",
        " 754: 'radio, wireless',\n",
        " 755: 'radio telescope, radio reflector',\n",
        " 756: 'rain barrel',\n",
        " 757: 'recreational vehicle, RV, R.V.',\n",
        " 758: 'reel',\n",
        " 759: 'reflex camera',\n",
        " 760: 'refrigerator, icebox',\n",
        " 761: 'remote control, remote',\n",
        " 762: 'restaurant, eating house, eating place, eatery',\n",
        " 763: 'revolver, six-gun, six-shooter',\n",
        " 764: 'rifle',\n",
        " 765: 'rocking chair, rocker',\n",
        " 766: 'rotisserie',\n",
        " 767: 'rubber eraser, rubber, pencil eraser',\n",
        " 768: 'rugby ball',\n",
        " 769: 'rule, ruler',\n",
        " 770: 'running shoe',\n",
        " 771: 'safe',\n",
        " 772: 'safety pin',\n",
        " 773: 'saltshaker, salt shaker',\n",
        " 774: 'sandal',\n",
        " 775: 'sarong',\n",
        " 776: 'sax, saxophone',\n",
        " 777: 'scabbard',\n",
        " 778: 'scale, weighing machine',\n",
        " 779: 'school bus',\n",
        " 780: 'schooner',\n",
        " 781: 'scoreboard',\n",
        " 782: 'screen, CRT screen',\n",
        " 783: 'screw',\n",
        " 784: 'screwdriver',\n",
        " 785: 'seat belt, seatbelt',\n",
        " 786: 'sewing machine',\n",
        " 787: 'shield, buckler',\n",
        " 788: 'shoe shop, shoe-shop, shoe store',\n",
        " 789: 'shoji',\n",
        " 790: 'shopping basket',\n",
        " 791: 'shopping cart',\n",
        " 792: 'shovel',\n",
        " 793: 'shower cap',\n",
        " 794: 'shower curtain',\n",
        " 795: 'ski',\n",
        " 796: 'ski mask',\n",
        " 797: 'sleeping bag',\n",
        " 798: 'slide rule, slipstick',\n",
        " 799: 'sliding door',\n",
        " 800: 'slot, one-armed bandit',\n",
        " 801: 'snorkel',\n",
        " 802: 'snowmobile',\n",
        " 803: 'snowplow, snowplough',\n",
        " 804: 'soap dispenser',\n",
        " 805: 'soccer ball',\n",
        " 806: 'sock',\n",
        " 807: 'solar dish, solar collector, solar furnace',\n",
        " 808: 'sombrero',\n",
        " 809: 'soup bowl',\n",
        " 810: 'space bar',\n",
        " 811: 'space heater',\n",
        " 812: 'space shuttle',\n",
        " 813: 'spatula',\n",
        " 814: 'speedboat',\n",
        " 815: \"spider web, spider's web\",\n",
        " 816: 'spindle',\n",
        " 817: 'sports car, sport car',\n",
        " 818: 'spotlight, spot',\n",
        " 819: 'stage',\n",
        " 820: 'steam locomotive',\n",
        " 821: 'steel arch bridge',\n",
        " 822: 'steel drum',\n",
        " 823: 'stethoscope',\n",
        " 824: 'stole',\n",
        " 825: 'stone wall',\n",
        " 826: 'stopwatch, stop watch',\n",
        " 827: 'stove',\n",
        " 828: 'strainer',\n",
        " 829: 'streetcar, tram, tramcar, trolley, trolley car',\n",
        " 830: 'stretcher',\n",
        " 831: 'studio couch, day bed',\n",
        " 832: 'stupa, tope',\n",
        " 833: 'submarine, pigboat, sub, U-boat',\n",
        " 834: 'suit, suit of clothes',\n",
        " 835: 'sundial',\n",
        " 836: 'sunglass',\n",
        " 837: 'sunglasses, dark glasses, shades',\n",
        " 838: 'sunscreen, sunblock, sun blocker',\n",
        " 839: 'suspension bridge',\n",
        " 840: 'swab, swob, mop',\n",
        " 841: 'sweatshirt',\n",
        " 842: 'swimming trunks, bathing trunks',\n",
        " 843: 'swing',\n",
        " 844: 'switch, electric switch, electrical switch',\n",
        " 845: 'syringe',\n",
        " 846: 'table lamp',\n",
        " 847: 'tank, army tank, armored combat vehicle, armoured combat vehicle',\n",
        " 848: 'tape player',\n",
        " 849: 'teapot',\n",
        " 850: 'teddy, teddy bear',\n",
        " 851: 'television, television system',\n",
        " 852: 'tennis ball',\n",
        " 853: 'thatch, thatched roof',\n",
        " 854: 'theater curtain, theatre curtain',\n",
        " 855: 'thimble',\n",
        " 856: 'thresher, thrasher, threshing machine',\n",
        " 857: 'throne',\n",
        " 858: 'tile roof',\n",
        " 859: 'toaster',\n",
        " 860: 'tobacco shop, tobacconist shop, tobacconist',\n",
        " 861: 'toilet seat',\n",
        " 862: 'torch',\n",
        " 863: 'totem pole',\n",
        " 864: 'tow truck, tow car, wrecker',\n",
        " 865: 'toyshop',\n",
        " 866: 'tractor',\n",
        " 867: 'trailer truck, tractor trailer, trucking rig, rig, articulated lorry, semi',\n",
        " 868: 'tray',\n",
        " 869: 'trench coat',\n",
        " 870: 'tricycle, trike, velocipede',\n",
        " 871: 'trimaran',\n",
        " 872: 'tripod',\n",
        " 873: 'triumphal arch',\n",
        " 874: 'trolleybus, trolley coach, trackless trolley',\n",
        " 875: 'trombone',\n",
        " 876: 'tub, vat',\n",
        " 877: 'turnstile',\n",
        " 878: 'typewriter keyboard',\n",
        " 879: 'umbrella',\n",
        " 880: 'unicycle, monocycle',\n",
        " 881: 'upright, upright piano',\n",
        " 882: 'vacuum, vacuum cleaner',\n",
        " 883: 'vase',\n",
        " 884: 'vault',\n",
        " 885: 'velvet',\n",
        " 886: 'vending machine',\n",
        " 887: 'vestment',\n",
        " 888: 'viaduct',\n",
        " 889: 'violin, fiddle',\n",
        " 890: 'volleyball',\n",
        " 891: 'waffle iron',\n",
        " 892: 'wall clock',\n",
        " 893: 'wallet, billfold, notecase, pocketbook',\n",
        " 894: 'wardrobe, closet, press',\n",
        " 895: 'warplane, military plane',\n",
        " 896: 'washbasin, handbasin, washbowl, lavabo, wash-hand basin',\n",
        " 897: 'washer, automatic washer, washing machine',\n",
        " 898: 'water bottle',\n",
        " 899: 'water jug',\n",
        " 900: 'water tower',\n",
        " 901: 'whiskey jug',\n",
        " 902: 'whistle',\n",
        " 903: 'wig',\n",
        " 904: 'window screen',\n",
        " 905: 'window shade',\n",
        " 906: 'Windsor tie',\n",
        " 907: 'wine bottle',\n",
        " 908: 'wing',\n",
        " 909: 'wok',\n",
        " 910: 'wooden spoon',\n",
        " 911: 'wool, woolen, woollen',\n",
        " 912: 'worm fence, snake fence, snake-rail fence, Virginia fence',\n",
        " 913: 'wreck',\n",
        " 914: 'yawl',\n",
        " 915: 'yurt',\n",
        " 916: 'web site, website, internet site, site',\n",
        " 917: 'comic book',\n",
        " 918: 'crossword puzzle, crossword',\n",
        " 919: 'street sign',\n",
        " 920: 'traffic light, traffic signal, stoplight',\n",
        " 921: 'book jacket, dust cover, dust jacket, dust wrapper',\n",
        " 922: 'menu',\n",
        " 923: 'plate',\n",
        " 924: 'guacamole',\n",
        " 925: 'consomme',\n",
        " 926: 'hot pot, hotpot',\n",
        " 927: 'trifle',\n",
        " 928: 'ice cream, icecream',\n",
        " 929: 'ice lolly, lolly, lollipop, popsicle',\n",
        " 930: 'French loaf',\n",
        " 931: 'bagel, beigel',\n",
        " 932: 'pretzel',\n",
        " 933: 'cheeseburger',\n",
        " 934: 'hotdog, hot dog, red hot',\n",
        " 935: 'mashed potato',\n",
        " 936: 'head cabbage',\n",
        " 937: 'broccoli',\n",
        " 938: 'cauliflower',\n",
        " 939: 'zucchini, courgette',\n",
        " 940: 'spaghetti squash',\n",
        " 941: 'acorn squash',\n",
        " 942: 'butternut squash',\n",
        " 943: 'cucumber, cuke',\n",
        " 944: 'artichoke, globe artichoke',\n",
        " 945: 'bell pepper',\n",
        " 946: 'cardoon',\n",
        " 947: 'mushroom',\n",
        " 948: 'Granny Smith',\n",
        " 949: 'strawberry',\n",
        " 950: 'orange',\n",
        " 951: 'lemon',\n",
        " 952: 'fig',\n",
        " 953: 'pineapple, ananas',\n",
        " 954: 'banana',\n",
        " 955: 'jackfruit, jak, jack',\n",
        " 956: 'custard apple',\n",
        " 957: 'pomegranate',\n",
        " 958: 'hay',\n",
        " 959: 'carbonara',\n",
        " 960: 'chocolate sauce, chocolate syrup',\n",
        " 961: 'dough',\n",
        " 962: 'meat loaf, meatloaf',\n",
        " 963: 'pizza, pizza pie',\n",
        " 964: 'potpie',\n",
        " 965: 'burrito',\n",
        " 966: 'red wine',\n",
        " 967: 'espresso',\n",
        " 968: 'cup',\n",
        " 969: 'eggnog',\n",
        " 970: 'alp',\n",
        " 971: 'bubble',\n",
        " 972: 'cliff, drop, drop-off',\n",
        " 973: 'coral reef',\n",
        " 974: 'geyser',\n",
        " 975: 'lakeside, lakeshore',\n",
        " 976: 'promontory, headland, head, foreland',\n",
        " 977: 'sandbar, sand bar',\n",
        " 978: 'seashore, coast, seacoast, sea-coast',\n",
        " 979: 'valley, vale',\n",
        " 980: 'volcano',\n",
        " 981: 'ballplayer, baseball player',\n",
        " 982: 'groom, bridegroom',\n",
        " 983: 'scuba diver',\n",
        " 984: 'rapeseed',\n",
        " 985: 'daisy',\n",
        " 986: \"yellow lady's slipper, yellow lady-slipper, Cypripedium calceolus, Cypripedium parviflorum\",\n",
        " 987: 'corn',\n",
        " 988: 'acorn',\n",
        " 989: 'hip, rose hip, rosehip',\n",
        " 990: 'buckeye, horse chestnut, conker',\n",
        " 991: 'coral fungus',\n",
        " 992: 'agaric',\n",
        " 993: 'gyromitra',\n",
        " 994: 'stinkhorn, carrion fungus',\n",
        " 995: 'earthstar',\n",
        " 996: 'hen-of-the-woods, hen of the woods, Polyporus frondosus, Grifola frondosa',\n",
        " 997: 'bolete',\n",
        " 998: 'ear, spike, capitulum',\n",
        " 999: 'toilet tissue, toilet paper, bathroom tissue'}"
      ],
      "execution_count": 90,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2jXDQpLLFJBP"
      },
      "source": [
        "# **ViT examples**"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gUaDXoRtNvZH"
      },
      "source": [
        "### ***Implementation of rules***"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "53pvONB1LLcl"
      },
      "source": [
        "# rule 5 from paper\n",
        "def avg_heads(cam, grad):\n",
        "    cam = cam.reshape(-1, cam.shape[-2], cam.shape[-1])\n",
        "    grad = grad.reshape(-1, grad.shape[-2], grad.shape[-1])\n",
        "    cam = grad * cam\n",
        "    cam = cam.clamp(min=0).mean(dim=0)\n",
        "    return cam\n",
        "\n",
        "# rule 6 from paper\n",
        "def apply_self_attention_rules(R_ss, cam_ss):\n",
        "    R_ss_addition = torch.matmul(cam_ss, R_ss)\n",
        "    return R_ss_addition\n",
        "\n",
        "def generate_relevance(model, input, index=None):\n",
        "    output = model(input, register_hook=True)\n",
        "    if index == None:\n",
        "        index = np.argmax(output.cpu().data.numpy(), axis=-1)\n",
        "\n",
        "    one_hot = np.zeros((1, output.size()[-1]), dtype=np.float32)\n",
        "    one_hot[0, index] = 1\n",
        "    one_hot_vector = one_hot\n",
        "    one_hot = torch.from_numpy(one_hot).requires_grad_(True)\n",
        "    one_hot = torch.sum(one_hot.cuda() * output)\n",
        "    model.zero_grad()\n",
        "    one_hot.backward(retain_graph=True)\n",
        "\n",
        "    num_tokens = model.blocks[0].attn.get_attention_map().shape[-1]\n",
        "    R = torch.eye(num_tokens, num_tokens).cuda()\n",
        "    for blk in model.blocks:\n",
        "        grad = blk.attn.get_attn_gradients()\n",
        "        cam = blk.attn.get_attention_map()\n",
        "        cam = avg_heads(cam, grad)\n",
        "        R += apply_self_attention_rules(R.cuda(), cam.cuda())\n",
        "    return R[0, 1:]"
      ],
      "execution_count": 91,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UtHosD9lCgAA"
      },
      "source": [
        "from baselines.ViT.ViT_new import vit_base_patch16_224 as vit\n",
        "\n",
        "normalize = transforms.Normalize(mean=[0.5, 0.5, 0.5], std=[0.5, 0.5, 0.5])\n",
        "transform = transforms.Compose([\n",
        "    transforms.Resize(256),\n",
        "    transforms.CenterCrop(224),\n",
        "    transforms.ToTensor(),\n",
        "    normalize,\n",
        "])\n",
        "\n",
        "# create heatmap from mask on image\n",
        "def show_cam_on_image(img, mask):\n",
        "    heatmap = cv2.applyColorMap(np.uint8(255 * mask), cv2.COLORMAP_JET)\n",
        "    heatmap = np.float32(heatmap) / 255\n",
        "    cam = heatmap + np.float32(img)\n",
        "    cam = cam / np.max(cam)\n",
        "    return cam\n",
        "\n",
        "# initialize ViT pretrained\n",
        "model = vit(pretrained=True).cuda()\n",
        "model.eval()\n",
        "\n",
        "def generate_visualization(original_image, class_index=None):\n",
        "    transformer_attribution = generate_relevance(model, original_image.unsqueeze(0).cuda(), index=class_index).detach()\n",
        "    transformer_attribution = transformer_attribution.reshape(1, 1, 14, 14)\n",
        "    transformer_attribution = torch.nn.functional.interpolate(transformer_attribution, scale_factor=16, mode='bilinear')\n",
        "    transformer_attribution = transformer_attribution.reshape(224, 224).cuda().data.cpu().numpy()\n",
        "    transformer_attribution = (transformer_attribution - transformer_attribution.min()) / (transformer_attribution.max() - transformer_attribution.min())\n",
        "    image_transformer_attribution = original_image.permute(1, 2, 0).data.cpu().numpy()\n",
        "    image_transformer_attribution = (image_transformer_attribution - image_transformer_attribution.min()) / (image_transformer_attribution.max() - image_transformer_attribution.min())\n",
        "    vis = show_cam_on_image(image_transformer_attribution, transformer_attribution)\n",
        "    vis =  np.uint8(255 * vis)\n",
        "    vis = cv2.cvtColor(np.array(vis), cv2.COLOR_RGB2BGR)\n",
        "    return vis\n",
        "\n",
        "def print_top_classes(predictions, **kwargs):    \n",
        "    # Print Top-5 predictions\n",
        "    prob = torch.softmax(predictions, dim=1)\n",
        "    class_indices = predictions.data.topk(5, dim=1)[1][0].tolist()\n",
        "    max_str_len = 0\n",
        "    class_names = []\n",
        "    for cls_idx in class_indices:\n",
        "        class_names.append(CLS2IDX[cls_idx])\n",
        "        if len(CLS2IDX[cls_idx]) > max_str_len:\n",
        "            max_str_len = len(CLS2IDX[cls_idx])\n",
        "    \n",
        "    print('Top 5 classes:')\n",
        "    for cls_idx in class_indices:\n",
        "        output_string = '\\t{} : {}'.format(cls_idx, CLS2IDX[cls_idx])\n",
        "        output_string += ' ' * (max_str_len - len(CLS2IDX[cls_idx])) + '\\t\\t'\n",
        "        output_string += 'value = {:.3f}\\t prob = {:.1f}%'.format(predictions[0, cls_idx], 100 * prob[0, cls_idx])\n",
        "        print(output_string)"
      ],
      "execution_count": 92,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 285
        },
        "id": "ZPbx6CIHEl08",
        "outputId": "30998618-83c7-48a9-8f06-d52127281f42"
      },
      "source": [
        "image = Image.open('samples/catdog.png')\n",
        "dog_cat_image = transform(image)\n",
        "\n",
        "fig, axs = plt.subplots(1, 3)\n",
        "axs[0].imshow(image);\n",
        "axs[0].axis('off');\n",
        "\n",
        "output = model(dog_cat_image.unsqueeze(0).cuda())\n",
        "print_top_classes(output)\n",
        "\n",
        "# cat - the predicted class\n",
        "cat = generate_visualization(dog_cat_image)\n",
        "\n",
        "# dog \n",
        "# generate visualization for class 243: 'bull mastiff'\n",
        "dog = generate_visualization(dog_cat_image, class_index=243)\n",
        "\n",
        "\n",
        "axs[1].imshow(cat);\n",
        "axs[1].axis('off');\n",
        "axs[2].imshow(dog);\n",
        "axs[2].axis('off');"
      ],
      "execution_count": 93,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Top 5 classes:\n",
            "\t282 : tiger cat       \t\tvalue = 10.559\t prob = 68.6%\n",
            "\t281 : tabby, tabby cat\t\tvalue = 9.059\t prob = 15.3%\n",
            "\t285 : Egyptian cat    \t\tvalue = 8.414\t prob = 8.0%\n",
            "\t243 : bull mastiff    \t\tvalue = 7.425\t prob = 3.0%\n",
            "\t811 : space heater    \t\tvalue = 5.152\t prob = 0.3%\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py:3063: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.\n",
            "  \"See the documentation of nn.Upsample for details.\".format(mode))\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 285
        },
        "id": "8lyV6PiIEspF",
        "outputId": "ee83ce5a-c36a-4cf9-e96f-6fc7cc0ffea6"
      },
      "source": [
        "image = Image.open('samples/el2.png')\n",
        "tusker_zebra_image = transform(image)\n",
        "\n",
        "fig, axs = plt.subplots(1, 3)\n",
        "axs[0].imshow(image);\n",
        "axs[0].axis('off');\n",
        "\n",
        "output = model(tusker_zebra_image.unsqueeze(0).cuda())\n",
        "print_top_classes(output)\n",
        "\n",
        "# tusker - the predicted class\n",
        "tusker = generate_visualization(tusker_zebra_image)\n",
        "\n",
        "# zebra \n",
        "# generate visualization for class 340: 'zebra'\n",
        "zebra = generate_visualization(tusker_zebra_image, class_index=340)\n",
        "\n",
        "\n",
        "axs[1].imshow(tusker);\n",
        "axs[1].axis('off');\n",
        "axs[2].imshow(zebra);\n",
        "axs[2].axis('off');"
      ],
      "execution_count": 94,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Top 5 classes:\n",
            "\t101 : tusker                              \t\tvalue = 11.216\t prob = 37.9%\n",
            "\t340 : zebra                               \t\tvalue = 10.973\t prob = 29.7%\n",
            "\t386 : African elephant, Loxodonta africana\t\tvalue = 10.747\t prob = 23.7%\n",
            "\t385 : Indian elephant, Elephas maximus    \t\tvalue = 9.547\t prob = 7.2%\n",
            "\t343 : warthog                             \t\tvalue = 5.566\t prob = 0.1%\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py:3063: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.\n",
            "  \"See the documentation of nn.Upsample for details.\".format(mode))\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 285
        },
        "id": "2o_lqvaZEzwR",
        "outputId": "7d9fce70-9b78-49db-b525-0ff628abd408"
      },
      "source": [
        "image = Image.open('samples/dogbird.png')\n",
        "dog_bird_image = transform(image)\n",
        "\n",
        "fig, axs = plt.subplots(1, 3)\n",
        "axs[0].imshow(image);\n",
        "axs[0].axis('off');\n",
        "\n",
        "output = model(dog_bird_image.unsqueeze(0).cuda())\n",
        "print_top_classes(output)\n",
        "\n",
        "# basset - the predicted class\n",
        "basset = generate_visualization(dog_bird_image, class_index=161)\n",
        "\n",
        "# generate visualization for class 87: 'African grey, African gray, Psittacus erithacus (grey parrot)'\n",
        "parrot = generate_visualization(dog_bird_image, class_index=87)\n",
        "\n",
        "\n",
        "axs[1].imshow(basset);\n",
        "axs[1].axis('off');\n",
        "axs[2].imshow(parrot);\n",
        "axs[2].axis('off');"
      ],
      "execution_count": 95,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Top 5 classes:\n",
            "\t161 : basset, basset hound         \t\tvalue = 10.514\t prob = 78.8%\n",
            "\t163 : bloodhound, sleuthhound      \t\tvalue = 8.604\t prob = 11.7%\n",
            "\t166 : Walker hound, Walker foxhound\t\tvalue = 7.446\t prob = 3.7%\n",
            "\t162 : beagle                       \t\tvalue = 5.561\t prob = 0.6%\n",
            "\t168 : redbone                      \t\tvalue = 5.249\t prob = 0.4%\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/torch/nn/functional.py:3063: UserWarning: Default upsampling behavior when mode=bilinear is changed to align_corners=False since 0.4.0. Please specify align_corners=True if the old behavior is desired. See the documentation of nn.Upsample for details.\n",
            "  \"See the documentation of nn.Upsample for details.\".format(mode))\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 3 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}